research methods design and analysis global edition 12th edition

Research Methods, Design, and Analysis, Global Edition 12th Edition

• Author(s) Larry B. Christensen; R. Burke Johnson; R. Burke Johnson; Lisa A. Turner
• Publisher Pearson (Intl)

Print ISBN 9781292057743, 1292057742

Etext isbn 9781292068466, 1292068469.

• Edition 12th
• Copyright 2015
• Available from $ 79.95 AUD SKU: 9781292068466

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Research Methods, Design, and Analysis, Global Edition 12th Edition is written by Larry B. Christensen; R. Burke Johnson; R. Burke Johnson; Lisa A. Turner and published by Pearson (Intl). The Digital and eTextbook ISBNs for Research Methods, Design, and Analysis, Global Edition are 9781292068466, 1292068469 and the print ISBNs are 9781292057743, 1292057742. Save up to 80% versus print by going digital with VitalSource.

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Research Methods, Design, and Analysis, Global Edition Paperback – 29 May 2014

Encourages mastery of the basic principles of psychological research

Research Methods, Design, and Analysis, 12th Edition provides an understanding of the research methods used to investigate human thought and behaviour. The coverage of experimental, qualitative, correlational, and survey research helps students develop their research skills for all aspects of psychology. Information is presented in a simple and straightforward manner and placed into context of actual research studies, helping students make real-life connections.

• ISBN-10 1292057742
• ISBN-13 978-1292057743
• Edition 12th
• Publisher Pearson
• Publication date 29 May 2014
• Language English
• Dimensions 19.51 x 3.12 x 23.5 cm
• Print length 542 pages
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• Publisher ‏ : ‎ Pearson; 12th edition (29 May 2014)
• Language ‏ : ‎ English
• Paperback ‏ : ‎ 542 pages
• ISBN-10 ‏ : ‎ 1292057742
• ISBN-13 ‏ : ‎ 978-1292057743
• Dimensions ‏ : ‎ 19.51 x 3.12 x 23.5 cm
• 177 in Psychology Research (Books)
• 1,744 in Psychology Textbooks
• 4,689 in Sociology (Books)

About the authors

Larry b. christensen.

Discover more of the author’s books, see similar authors, read author blogs, and more

Burke Johnson

Burke Johnson is a professor in the Professional Studies Department at the University of South Alabama. His PhD is from the REMS (research, evaluation, measurement, and statistics) program in the College of Education at the University of Georgia. He also has graduate degrees in psychology, sociology, and public administration, which have provided him with a multidisciplinary perspective on research methodology. He was guest editor for a special issue of Research in the Schools focusing on mixed research (available online at www.msera.org/rits_131.htm) and completed a similar guest editorship for the American Behavioral Scientist. He was an associate editor of the Journal of Mixed Methods Research. Burke is first author of Educational Research: Quantitative, Qualitative, and Mixed Approaches (Sage, 2014, 5th edition); second author of Research Methods, Design, and Analysis (Pearson, 2014, 12th edition); coeditor (with Sharlene Hesse-Biber) of The Oxford Handbook of Multimethod and Mixed Methods Research Inquiry (2015); coeditor (with Paul Vogt) of Correlation and Regression Analysis (2012); and associate editor of The SAGE Glossary of the Social and Behavioral Sciences (2009).

Lisa Anne Turner

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How to use MoSCoW in UX research and avoid featuritis

Eva Schicker

UsabilityGeek

UX Design Essentials: Article 11

What is MoSCoW?

MoSCoW is the acronym for a concept called M ust Have/ S hould Have/ Co uld Have/ W ould Have. This conceptual tool is used to analyze the ranking of your product’s features.

What is featuritis?

Featuritis is the condition of Too Many Product Features . This condition arises when stakeholder and/or design teams add too many buttons, clicks, turns, or knobs to their product. This leaves the consumer utterly confused and overwhelmed, and thereby unable to use the product properly.

To prioritize product features, and avoid featuritis, we use the MoSCoW analytics tool at the beginning of the product’s design phase (or towards the end of the research phase)

What is the concept of a moscow analysis.

MoSCoW is a research/design method that gives you a visual insight into how to prioritize your product’s features

MoSCoW is represented with this four-quadrant chart, each quadrant representing types of features in order of priority, in clock-wise ranking of priority:

Written by Eva Schicker

Hello. I write about UX, UI, AI, animation, tech, fiction & art through the eyes of a designer & painter. I live in NYC. Book author, UX Grad GA NYC.

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World Leaders in Research-Based User Experience

5 prioritization methods in ux roadmapping.

November 14, 2021 2021-11-14

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Prioritizing work into a roadmap can be daunting for UX practitioners. Prioritization methods base these important decisions on objective, relevant criteria instead of subjective opinions.

This article outlines 5 methods for prioritizing work into a UX roadmap :

• Impact–effort matrix 
• Feasibility, desirability, and viability scorecard
• RICE method
• MoSCoW analysis 

These prioritization methods can be used to prioritize a variety of “items,” ranging from research questions, user segments, and features to ideas, and tasks. This article focuses on using these methods within the context of roadmapping—prioritizing problems that need to be solved into a strategic timeline. 

In This Article:

1. impact–effort matrix, 2. feasibility, desirability, and viability scorecard , 3. rice method, 4. moscow analysis, 5. kano model, 1.a. overview.

An impact–effort matrix is a 2D-visual that plots relative user value against implementation complexity. Variations of this matrix are used across various product-development approaches, including Six Sigma, design thinking, and Agile.

The resulting matrix captures the relative effort necessary to implement candidate features and their impact on the users. It can be subdivided into four quadrants: 

• Quick wins include low-effort, high-impact items that are worth pursuing. 
• Big bets include high-effort, high-value items; they should be carefully planned and prototyped, and, if executed, are likely to be differentiators against competitors. 
• Money pit includes low-impact, high-effort items that are not worth the business investment; there are better places to spend time and resources. 
• Fill-ins comprise low-effort, low-impact items that may be easy to implement but may not be worth the effort as their value is minimal. 

A comparative matrix is a malleable tool. While we discuss impact–effort matrices in this article, you can easily replace each axis with other criteria or use multiple matrices to assess more than two criteria. When setting up multiple matrices, set up your axes so that the Quick Wins (or whatever the equivalent best-outcome quadrant is) is positioned in the same spot (for example, always in the bottom left position), in order to easily compare several matrices and identify the items that consistently fall in best-outcome quadrant. 

1.B. Criteria

This prioritization method uses two primary criteria to rank features that are considered for implementation: the impact that the feature will have on the end user and the effort required to implement that feature. 

• Impact is the value the item will bring to the end user. The level of impact an item will have on end users depends on the users’ need, their alternatives, and the severity of the pain point the item solves.
• Effort is the amount of labor and resources required to solve the problem. The more technically complex the item, the higher effort it will require.

1.C. Process

Items are gathered on a whiteboard and their relative scores on the impact and effort dimensions are established through voting. Team members are given colored dots (one color per dimension) to vote for those items that they consider to rate highly on one or both dimensions.  

A general rule of thumb is that the number of votes per person is half the number of items being prioritized. It’s also possible that certain team members vote on a single dimension, according to their expertise — for example, UX professionals may rank impact, while developers may rank implementation effort.

After team members have silently voted on items, the items can be placed collaboratively on an effort–impact matrix (the x-axis represents effort, while the y-axis represents impact) according to the number of impact and effort votes received. 

Once everything is placed onto the chart, discuss the results and compare items, prioritizing those in the quick-wins and big-bets quadrants. Feel free to use the artifact as a platform for negotiation — throughout discussion with the team, it’s okay to collaboratively move items. However, at the end, there should be agreement on the final placement and the artifact should be documented and saved so it can easily be referenced in the future. 

1.D. Best for Quick, Collaborative Prioritization

An impact–effort matrix is best suited for quick, collaborative prioritizations. The method has a few advantages:

• The output is a shared visual that aligns mental models and builds common ground . 
• It is democratic — each person can express their own opinion through a vote.
• It can be done relatively quickly due to its simplicity. 

2.A. Overview

This method was developed by IDEO in the early 2000s. It ranks items based on a sum of individual scores across three criteria: feasibility, desirability, and viability. 

2.B. Criteria  

This prioritization method uses three criteria to rank items (i.e., features to be implemented):

• Feasibility : the degree to which the item can be technically built. Does the skillset and expertise exist to create this solution?
• Desirability : how much users want the item. What unique value proposition does it provide? Is the solution fundamentally needed, or are users otherwise able to accomplish their goals? 
• Viability : if the item is functionally attainable for the business.  Does pursuing the item benefit the business? What are the costs to the business and is the solution sustainable over time? 

2.C. Process

Create a table, with one row for each possible item, and columns for the 3 criteria — feasibility, desirability, and viability. Then, determine a numeric scoring scale for each criterion. In the example above, we used a numeric scale from 1 to 10, with 1 being a low score. 

Next, give each item a score across each criterion. Scoring should be as informed as possible — aim to include team members who have complementary expertise. Once each item is scored across each criterion, calculate its total score and force a rank. Sort the table from highest to lowest total score, then discuss the results with your team. 

2.D. Best for Customized Criteria 

This scorecard format is highly customizable. You can add columns to reflect criteria specific to your organization’s context and goals. You can also replace the criteria with others relevant to you. For example, the NUF Test , created by Dave Gray, uses the same scorecard format, but with New , Useful , Feasible as the criteria set. 

Another common modification is assigning weights to the different criteria — with those that are very important weighing more heavily in the final score. 

3.A. Overview

RICE is a prioritization framework developed by Intercom . It takes into account four factors: reach, impact, confidence, and effort to prioritize which features to implement.

3.B. Criteria  

This RICE method is based on scoring each item on 4 different dimensions:

• Reach : the number of users the item affects within a given time period 
• Impact : the value added to users 
• Confidence : how confident you are in your estimates of the other criteria (for example, highly confident if multiple data sources support your evaluation) 
• Effort : the amount of work necessary to implement the item 

3.C. Process

Using the RICE method is straightforward. Separate scores are assigned for each criterion, then an overall score is calculated. 

• A reach score is often estimated by looking at the number of users per time period (e.g., week, year);  ideally, this number is pulled from digital analytics or frequency metrics . 
• The impact score should reflect how much the item will increase delight or alleviate friction; it is hard to precisely calculate, and, thus, it’s usually assigned a score (for example, through voting, like in the previous methods) often on a scale from .25 (low) to 3 (high).  
• The confidence score is a percentage that represents how much you and your team trust the reach and impact scores.  100% represents high confidence, while 25% represents wild guesses. 
• The effort score is calculated as “person-months” — the amount of time it will take all team members to complete the item. For example, an item is 6 person-months if it would require 3 months of work from a designer and 1 month from 3 separate developers.  

Once you have each of the 4 criterion scores, use the formula to calculate the final score for each item: multiply the reach, impact, and confidence scores and divide the result by the effort score. Then compare, discuss, and reevaluate all the items’ scores with your team.  

3.D. Best for Technical-Oriented Teams

The RICE method works well for organizations that are more technical in nature (for example, when stakeholders are comfortable with equations or spreadsheets). The RICE method also works well when there are many items that need to be prioritized. Consider including peers with diverse domains of expertise in the RICE process and assign them the task of calculating the score for the criterion that relates to their expertise. 

4.A. Overview

MoSCoW analysis is a method for clustering items into four primary groups: Must Have , Should Have , Could Have , and Will Not Have . It was created by Dai Clegg and is used in many Agile frameworks. 

4.B. Criteria

This prioritization approach groups items into four buckets: 

• Must have : items that are vital to the product or project. Think of these as required for anything else to happen. If these items aren’t delivered, there is no point in delivering the solution at all. Without them the product won’t work, a law will be broken, or the project becomes useless. 
• Should have: items that are important to the project or context, but not absolutely mandatory. These items support core functionality (that will be painful to leave out), but the project or product will still work without them. 
• Could haves : items that are not essential, but wanted and nice to have. They have a small impact if left out. 
• Will not have: items that are not needed. They don’t present enough value and can be deprioritized or dropped. 

4.C. Process

MoSCoW analysis can be applied to an entire project (start to finish) or to a project increment (a sprint or specific time horizon). 

Begin by identifying the scope you are prioritizing items for. If your goal is to create a UX roadmap, you’ll usually have to prioritize for the first three time horizons: now (work occurring in the next 2 months), next (work occurring in the next 6 months), and future (work occurring in the next year). 

Compile the items being prioritized and give each team member 3 weighted voting dots, (one dot with a 1 on it, the next with a 2 on it, and so forth). Ask team members to assign their dots to the items they believe most important, with 3 being weighed most heavily.

Add up each item’s score based on the ranked votes (3 = 3 points and so forth). Identify the items with the highest scores and make sure that everybody in the group agrees on their importance. 

As each item is discussed and agreed upon as a Must Have , move it to a new dedicated space. Repeat this process for lower-priority items and assign them to the Should Have, Could Have , and Will Not Have groups based on their scores.

Once you have assigned each item to one of the four groups, establish the resources and bandwidth required for each group, starting with the Must Haves . Keep track of the total bandwidth and resources at your disposal, distributing and allocating your total amount across Must Haves (which should get the most resources), Should Haves (with the second most resources), and finally Could Haves (with few resources).  

There is not a clear threshold for how many items should be in each group. To determine this number, return to the goal of the prioritization activity. For example, if you are prioritizing items in a backlog, there is only time for so many tasks to be achieved in one sprint. In this scenario, all Must Haves should be easily achieved within one sprint; this constraint will limit how many items cannot be placed within this group.  

4.D. Best for Teams with Clear Time Boxes

MoSCoW is a good prioritization method for teams looking for a simplified approach (given the relatively vague prioritization criteria set) and with a clear time box identified for the work. Without a clearly scoped timeline for completing the work,  teams run the risk of overloading the Must Haves (of course, everything will feel like a Must Have if the timeline is the next two years!). 

5.A. Overview

The Kano model was published by Dr. Noriaki Kano in 1984 and is a primary prioritization method in the Six Sigma framework. Items are grouped into four categories according to user satisfaction and functionality and plotted on a 2D graph. 

5.B. Criteria 

This prioritization method uses two primary criterions to rank items: functionality and satisfaction. 

• None (-2) : the solution cannot be implemented
• Some (-1) : the solution can be partly implemented
• Basic (0) : the solution’s primary functions can be implemented, but nothing more 
• Good (1) : the solution can be implemented to an acceptable degree
• Best (2) : the solution can be implemented to its full potential 
• Frustrated (-2) : the solution causes additional hardship for the user
• Dissatisfied (-1) : the solution does not meet users’ expectations
• Neutral (0)  
• Satisfied (1) : the solution meets users’ expectations
• Delighted (2) : the solution exceeds users’ expectations

5.C. Process

Each item is first assigned a satisfaction score and a functionality score. The satisfaction score should be based on user data — for example, on existing user research or on a top-task user survey asking users to rate the importance of each feature; the functionality score can be rooted in the collective expertise of the team.  

These scores are then used to plot items onto a 2D-graph, with the x-axis corresponding to functionality and the y-axis to satisfaction. Each axis goes from -2 to 2. 

Based on their placement on their scores, items fall into one of four categories: 

• The Attractive category (often called Excitement ) are items that are likely to bring a considerable increase in user delight. A characteristic of this category is the disproportionate increase in satisfaction to functionality. Your users may not even notice their absence (because they weren’t expectations in the first place), but with good-enough implementation, user excitement can grow exponentially. The items in the Attractive are those with a satisfaction score of 0 or better. These items appear above the blue Attractive line in the Kano illustration above.
• The Performance category contains items that are utilitarian. Unlike other categories, this group grows proportionately. The more you invest in items within this category, the more customer satisfaction they are likely to prompt. The items in the Performance category have equal satisfaction and performance scores and fall on the green line in the Kano illustration above.  
• The Indifferent category contains items that users feel neutral towards — satisfaction does not significantly increase or decrease with their functionality and is always 0. Regardless of the amount of investment put into these items, users won’t care. These items are all placed on the dark blue Indifference line (which overlaps with the x-axis). 
• The Must-be category are basic items that are expected by users. Users assume these capabilities exist. They are unlikely to make customers more satisfied, but without them, customers will be disproportionately dissatisfied. Items fall into the Must-be category when their satisfaction score is 0 or worse. These are the items in the purple area of the Kano diagram, below the purple Must Be line.

Once items are assigned to groups, make sure that everybody in the team agrees with the assignment. Items with scores of (0,0), (-2,0) and (+2,0) may initially belong to two groups. In these cases, discuss the item and ask yourself if user value will grow proportionately with your team’s investment. If the answer is yes, group the item with Performance . In cases this is false, group the item with Indifferent . 

Move items as needed, then prioritize items into your roadmap. Items in the Performance category should have the highest priority, followed by Must be , Attractive , then Indifferent . 

5.D. Best for Forcing a User-Centric Prioritization 

The Kano model is a good approach for teams who have a hard time prioritizing based on the user — often due to politics or a traditional development-driven culture. The Kano model introduces user research directly into the prioritization process and mandates discussion around user expectations.  

There are many more prioritization methods, aside from the five mentioned in this article. (It’s also easy to imagine variations on these 5.) One method is not better than another. Consider your project’s context, team culture, and success criteria when choosing a prioritization approach. 

Once you find an approach that works, don’t be afraid to iterate — adjust and adapt it to fit to your needs or appeal to your team. Involve others in this process. The best prioritization methods are ones that everyone on your team, including stakeholders, buy into. 

McBride, S. (2018). RICE: Simple prioritization for product managers. Intercom.  https://www.intercom.com/blog/rice-simple-prioritization-for-product-managers/

What is the Kano Model? ProductPlan.  https://www.productplan.com/glossary/kano-model/

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• What is the MoSCoW prioritization method?

Last updated

17 April 2024

Reviewed by

Mary Mikhail

Several techniques are available to project managers to plan a team’s workload by ranking projects or tasks by significance. These prioritization techniques also help communicate to project teams and stakeholders where resources must be directed to accomplish goals. 

The MoSCoW method is one such popular prioritization technique. Learn what the MoSCoW method is and how to apply it. 

The MoSCoW method ranks the significance of a task by determining the requirements for a project's successful completion.

Some may be essential and must be included in the project’s deliverables. You may find other specifications are not required for a successful conclusion, but you might consider them to improve the result or business value.

This prioritization technique requires you to classify projects and tasks by their levels of necessity in reaching your goal.

• Where does the term MoSCoW come from?

MoSCoW is an acronym that signifies the names of the categories in which the requirements are placed:

M = Must-haves

S = Should-haves

C = Could-haves

W = Will not have at this time or wish for

The Os were added to make the acronym easier to pronounce. Using these categories makes projects more manageable, helps with better resource control, and increases the chances of meeting deadlines.

• Using MoSCoW prioritization categories

Requirements with the highest level of importance are must-haves. You'll place lesser-ranked requirements in the should-haves and could-haves categories. Anything in the will-not-have category defines the requirement as nice to have, but not a necessity, at least for now.

Deliverance of effective solutions

Because a project can't be accomplished without must-have initiatives, your team must be committed to completing these requirements.

Should-haves

These tasks or elements are important to completing the project or product, but they're not necessary. Although the product will still function without should-have requirements, you shouldn't disregard them or underestimate their importance because they can significantly increase the product's value.

Performance improvements and new functions are examples of should-have requirements.

Could-haves

These initiatives take a back seat to must-haves and should-haves. If left out, they will not significantly influence the completion of a product or project. A could-have element is desired but not necessary.

Will-not-haves (at this time)

The items in this category set realistic expectations for what the product will not include. A clear visual representation of these requirements communicates to the team and stakeholders items identified as out of scope.

What do your users really want?

Just upload your customer research and ask your insights hub - like magic.

• When do you use the MoSCoW method for prioritization?

The idea behind Agile project management is to decrease the risk of missed goals and deadlines. It uses resources and time more efficiently by breaking the project into smaller sections and prioritizing tasks, requirements, products, and stories.

To prioritize these, you can use the MoSCoW method within the scope of an Agile project.

• What is an example of the MoSCoW technique?

Imagine you're building an e-commerce website that must launch by a specific date. You'll have to prioritize its features because you don't have unlimited time to work on the site.

The functionality you want to incorporate into the website could be:

Users can log onto the website

Users should have access to a "Forgot Password" solution

Users can change account details

Users can send an email to the system requesting a change to the account page

Here's how you might categorize these features based on how effective you want the website to be and the time constraints you face:

Must-haves:

Should-haves:

Could-haves:

Will-not-haves

Users can click on a phone number on the webpage, and a call will automatically be made from their desk phone to that number

• Benefits of using MoSCoW prioritization

MoSCoW prioritization offers several benefits in project management:

Clarity and focus: It helps teams identify and prioritize the most critical requirements, ensuring clarity on what needs to be delivered first.

Efficiency: By categorizing tasks into must-haves, should-haves, could-haves, and won't-haves, teams can allocate resources more efficiently and focus on delivering essential features first.

Stakeholder alignment: It facilitates stakeholder discussions by providing a common language to discuss and prioritize requirements, ensuring alignment on project goals and objectives.

Risk mitigation: MoSCoW prioritization helps mitigate project risks by addressing must-have requirements first, reducing the likelihood of critical features being overlooked or delayed.

Flexibility: It allows for flexibility in project planning and execution by accommodating changes in requirements throughout the project lifecycle while ensuring that essential features are prioritized.

Time and cost savings: By focusing on must-have requirements early in the project, teams can deliver value more quickly, potentially reducing project timelines and costs.

Overall, MoSCoW prioritization promotes a structured and systematic approach to project management, leading to more successful and efficient project outcomes.

• Disadvantages of using MoSCoW prioritization

The major disadvantage of the MoSCoW method is that it isn’t an objective or consistent scoring system. For this methodology to be effective, other scoring systems, like the weighted scoring or the Kano model, should be used in conjunction with it.

Not combining another scoring system with the MoSCoW method can exclude the organization's leadership from the decision-making process. Decisions would then be in danger of being made based on the project manager's personal preferences rather than adhering to business goals and values.

This method does not involve supporting reasoning on how you prioritize requirements within the same category or why one requirement is a must-have or should-have. The parameters of each category can be blurred. There is also uncertainty about whether will-not-haves are being left out of the tasks required now or out of the entire project.

• How can teams use MoSCoW to their advantage?

Resources, time, and skill sets are not unlimited in the business world. You must constantly strive to work around those constraints efficiently for a maximum return on investment (ROI). Using the MoSCoW method can help.

Use budgetary constraints to prioritize

Some projects have tight budgets. You can use the MoSCoW method by using the budget to determine which items must be and should be completed.

Use the team's skill sets to prioritize

Experience and expertise levels can help determine which tasks to prioritize. If a task requires skills that the team lacks, you must prioritize it accordingly.

Use the competing needs of the company to prioritize

While your team is working on a specific aspect of a project, the company's leaders may have added additional requirements for your team to complete within the same timeframe. You would then have to reshuffle the priorities to accommodate the additional requirements. The MoSCoW method can help you do this.

• Best practices for using MoSCoW prioritization

Include all stakeholders in using the MoSCoW method, from the executive level down to the different teams involved in the successful completion of the project. Get them to also use objective scoring systems like:

Opportunity scoring: uses data from market research to determine what customers expect from your product or service. Prioritization is done according to their wants and needs.

Priority poker: based on priorities that will provide the highest yields in a specific target market. The marketing team, executive team, and customers should be involved for accurate ranking of priorities.

Cost of delay: based on determining how much money the company is losing by waiting to work on a particular task, product, or feature.

100-point method: all stakeholders vote for what they think is the most important requirement. They each get 100 points to distribute among the requirements, ranking them from most important to least. If a stakeholder thinks four requirements are of equal value, they can allocate 25 points to each. If they feel strongly that one requirement overrides all others, they can put all 100 points on that requirement.

Incorporate the data you receive from these scoring systems when inserting the requirements in your MoSCoW categories. Share the results with stakeholders so that they can understand why you prioritized the criteria as you did. This exercise might even reveal a reason to expand a budget constraint or allocate more resources to a priority the stakeholders initially thought unimportant.

How the MoSCoW method differs from the 100-point method

While the 100-point method helps in general brainstorming sessions, the MoSCoW method focuses on working within budget and time constraints.

Once the teams and stakeholders reach an agreement (perhaps by using the 100-point method) on the importance level of each requirement, the product managers or owners will use the MoSCoW method to categorize requirements based on:

High customer value

An elevated benefit to the business

Simple implementation

Inflated costs, when not applied as soon as possible

Technical specifications that are interdependent 

This will help stakeholders and project teams visualize the intended direction.

• MoSCoW prioritization in Agile project management

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When deciding on projects that will help increase revenue, decrease operational costs, boost productivity, or heighten customer satisfaction, you must choose the projects and project requirements that will most impact the goals you find important. The MoSCoW method can help you do just that.

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Moscow Method

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Research Methods, Design, and Analysis, Global Edition Paperback – International Edition, 29 May 2014

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Encourages mastery of the basic principles of psychological research

Research Methods, Design, and Analysis, 12/e, provides an understanding of the research methods used to investigate human thought and behavior. The coverage of experimental, qualitative, correlational, and survey research helps students develop their research skills for all aspects of psychology. Information is presented in a simple and straightforward manner and placed into context of actual research studies, helping students make real-life connections.

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• ISBN-10 1292057742
• ISBN-13 978-1292057743
• Edition 12th
• Publisher Pearson Education Limited
• Publication date 29 May 2014
• Language English
• Dimensions 19.51 x 3.12 x 23.5 cm
• Print length 544 pages
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Product details

• Publisher ‏ : ‎ Pearson Education Limited; 12th edition (29 May 2014)
• Language ‏ : ‎ English
• Paperback ‏ : ‎ 544 pages
• ISBN-10 ‏ : ‎ 1292057742
• ISBN-13 ‏ : ‎ 978-1292057743
• Dimensions ‏ : ‎ 19.51 x 3.12 x 23.5 cm
• #228 in Psychology Research
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